Thomas Henson

Tips & Tricks for Studying Machine Learning Projects

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How to Study Machine Learning Through Projects

Studying Machine Learning can seem overwhelming! Over our careers as developer or technologist we are constantly having to learning new skills. Whether you are  Database Administrator who needs to learn about Hadoop or Web Developer looking to learn JavaScript. Change is enviable and the way to change is through learning.  In fact many developers in the community advocate for making learning a daily or weekly habit of 1 – 2 hours every week. In today’s episode of Big Data Big Questions we explore my tips and tricks for learning Machine Learning (ML) or any other new technology.

Studying Machine Learning

Tips and Ticks for Studying Machine Learning

Make sure to watch the full video where I break down my tips and tricks for learning Machine Learning.

 

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Ultimate List of Tensorflow Resources for Machine Learning Engineers

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Tensorflow is the most popular deep learning/machine learning framework right now. One of the biggest reasons for the popularity of Tensorflow (and my personal favorite) is the portability. A Machine Learning Engineer can create models using Tensorflow on their local machine then deploy those same models to 100s or 1000s of machines. Another reason for the popularity is because the Tensorflow is primarily used with Python. Developers both old and new having been shifting to Python for the last 10 years, which means there is a huge talent pool out there ready to develop in Tensorflow.
The Google Brain team is primarily responsible for releasing the first iterations of Tensorflow (DistBelief prior to release). In 2015 Google released Tensorflow to the open source community and the development has only continued at scale. Considering the importance and popularity of Tensorflow I thought it was a good idea to create a resource list for Tensorflow learning/training/research.

Tensorflow Resources

Course on Tensorflow

Run Tensorflow in 10 Minutes with TFLearn – TFLearn offers machine learning engineers the ability to build Tensorflow neural networks with minimal use of coding. In this course, Implementing Multi-layer Neural Networks with TFLearn, you’ll learn foundational knowledge and gain the ability to build Tensorflow neural networks. First, you’ll explore how deep learning is used to accelerate artificial intelligence. Next, you’ll discover how to build convolutional neural networks. Finally, you’ll learn how to deploy both deep and generative neural networks. When you’re finished with this course, you’ll have the skills and knowledge of deep learning needed to build the next generation of artificial intelligence.

Research Topics on Tensorflow

Tensorflow – Official site for all things Tensorflow including downloading and installing. Read through the documentation and getting started guide. For a 15 hour deep dive into Tensorflow go through the Machine Learning Crash Course. 15 hours sounds like a lot but break it up into 30 minutes a day for 30 days. After 30 days you’ll have more of an understanding of ML/DL with Tensorflow than most of the competition.
Tensorflow Source Code – At some point in your Tensorflow journey you may want to jump directly into the source code. Tensorflow is an open source project and like most popular open source projects it’s on GitHub.
Tensorflow Resources

Hands On Tensorflow Resources

Tensorflow Playground – Interactive Neural Network inside the browser. It allows you to train data from 4 different data sets. You can control features, neurons, learning rate, activation, regularization, etc. One of the easiest things to try is running the same data type through the different activations to see which is faster.
JavaScript Tensorflow? – At first glance I didn’t realize the potential of having a JavaScript Library for Tensorflow. What benefit would come from training models in the browsers? After playing around with some of the demos (Pac-Man) on Tensorflow.js I started to understand how this can open doors to better game develop, human-computer interaction, and more.
Hands-On Machine Learning with Scikit-Learn & Tensorflow – Shamelessly stole this recommendation from a colleague. Should this be on the list for the Big Data Beard Book Club? I think so!
Docker Tensorflow – Super simple way to get started using Tensorflow. Data Engineers can pull Docker tensorflow/tensorflow  then pick CPU or GPU to get started developing with Tensorflow. I’ll say it again….a super simple way to get up and coding with Tensorflow. Go download it right now!!
Tensorflow Resources

Tensorflow Resources Video

Why Tensorflow is Awesome for Machine Learning – Since I created this list I’m definitely going to put my video at the top of the Tensorflow video. In this video I breakdown Tensorflow was a monumental tool for Deep Learning and Machine Learning.
Siraj Raval YouTube – Siraj Raval has a huge following on his YouTube Channel which is all about Machine Learning, Artificial Intelligence, and Deep Learning concepts. Checkout his first video on Tensorflow in 5 minutes for a quick high level overview of Tensorflow. Then watch my favorite Tensorflow video of creating an image classifier for training a model to detect is this picture of Darth Vader or not.
What is missing? Do you have a suggestion for a resource that should be added? Make sure to put those suggestions for Tensorflow resources in the comment section below.

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